Generic distributed processing for multi-agent systems

ABSTRACT

Generic Distributed Processing Unit (DPU) for Multi-Agent Systems (MAS) provides a Machine to Machine (M2M) interface that is fast, flexible, redundant and scalable. It allows the handling of unlikely edge cases that Human Machine Interfaces (HMI) cannot. It also allows the processing of excessive amounts of ancillary data that are not processed easily with an HMI arrangement. In the digital ecosystem, any like DPU can back up any other, making the system exceedingly robust.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/523,701 filed Oct. 24, 2014, now U.S. Pat. No. 9,569,289; which is acontinuation of U.S. patent application Ser. No. 14/171,143 filed Feb.3, 2014, now U.S. Pat. No. 8,898,218; which claims benefit of U.S.Provisional Patent Application No. 61/759,864 filed Feb. 1, 2013. Thedisclosures of the prior applications are incorporated herein in theirentirety by reference.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

None.

FIELD

The technology herein relates to multi-agent processing, and to systemsand methods providing robust coordination and control for multi-agentarchitectures.

BACKGROUND

Many industries use distributed, heterogeneous systems to make up largermulti-agent ecosystems. For the most part, coordination of these systemsis managed manually with the control agents being humans. In some cases,humans cannot react fast enough. In other cases, the solution is notsufficiently robust and does not have an adequate backup. Also, humanbased systems are generally hard to scale. Facilities for humans areexpensive to build and take time to construct. Training people forcomplex tasks is expensive, takes time and may not be possible orentirely effective for critical, rarely encountered edge cases. Indisaster situations, these limitations can compound already tryingsituations.

Many existing systems, for the most part, work with heterogeneousequipment or a subset of all the equipment, and have little automation.Some solutions are not sufficiently flexible and have a concept ofcentralized control with a single master server/process. Other systemsalso depend on a Human Machine Interface (HMI) that requires users toprocess large data sets quickly. Still other solutions are notsufficiently robust due to manual processes, single point of failureand/or minimal redundancy. Most solutions have poor heterogeneoussupport working for one vendor and/or long lead times for new support.

The technology herein addresses these and other problems.

BRIEF DESCRIPTION OF THE DRAWINGS

The following detailed description of exemplary non-limitingillustrative embodiments is to be read in conjunction with the drawingsof which:

FIGS. 1 and 1A are block diagrams of example non-limiting simplifiedsystems;

FIGS. 2A-2D are more detailed block diagrams of the example non-limitingsystem;

FIGS. 3A-3C are constellation diagrams of example non-limiting systems;

FIGS. 4A-4B show example non-limiting adaptability of the system;

FIG. 5 shows example non-limiting Agent Adapter DPU registration;

FIG. 6 is a more detailed diagram of example non-limiting eventprocessing;

FIG. 7 shows a simplified view of Event Processor to Reactor (DPUinternal) registration;

FIG. 8 is an example non-limiting flowchart;

FIG. 9 is an example non-limiting data flow and timing diagram;

FIG. 10 is an additional example non-limiting data flow and timingdiagram; and

FIG. 11 shows an example non-limiting vehicle application.

DETAILED DESCRIPTION OF EXAMPLE NON-LIMITING EMBODIMENTS

The technology herein provides a generic Distributed Processing Unit(DPU) for use in a wide area Multi-Agent Systems (MAS) architecture.This solution can be applied to a MAS of any size, from a single microor other processor to a digital ecosystem spanning the globe. Examplenon-limiting embodiments provide unified control over a collection ofdiscrete elements and/or acts as a System of Systems (SoS) controllingother control systems. DPU technology can also be applied recursively orcontain a hierarchy of implementations. In this way, the DPU can be aframework for creating a digital MAS and can be used to create Software,Hardware or hybrid Agents to control existing System Elements. Exampleembodiments react to conditions created either by events in thecontrolled digital ecosystem or external events that will affect thatdigital ecosystem.

In more detail, a distributed processing and control architecture cancomprise a number of intelligent or other elements distributed across anetwork, geography, an enterprise or any other domain. Intelligentelements such as Agents and/or Agent Adapters may generate and supplyevents for handling by the distributed processing and controlarchitecture. For example, such Agents and/or Agent Adapters mayinterface with machines or other apparatus of any type, complexity orfunctionality. In one example non-limiting implementation, the Agentsand/or Agent Adapters may discover distributed processing units by forexample setting up intentional race conditions and determining lowestresponse latency. Example distributed processing unit event processingcan include for example:

receiving an event from an agent;

transforming the event;

dispatching event to handlers;

handling the event;

discovering a further agent; and

sending the agent commands for action and response.

FIG. 1 shows a non-limiting example of a simplified distributingprocessing system of the type described above. FIG. 1 shows that anynumber of DPUs 12(1), 12(2), . . . 12(n) can communicate with one ormore machines M. Machine M can be any form of controller, agent, AgentAdapter, and/or system of arbitrary breadth and/or complexity. As onespecific example, machine M can comprise a node associated with a powerdelivery network.

In the example shown, each DPU 12 has or communicates with an associateddatabase DB. Thus, DPU 12(1) can access database DB(1), DPU 12(2) canaccess database DB(2), and DPU 12(N) can access database DB(N) (N can beany integer greater than one). In one embodiment, database DB(1) islocal to DPU 12(1), database DB(2) is local to DPU 12(2) and so on. Asshown in FIG. 1, a communications path C can exist between the databasesDB(1), DB(2), . . . DB(N). Communications path C can comprise any typeof path including wired, wireless, networked, optical, radio, local,long distance, wide area, the Internet, sneaker net, telephone or anyother kind of path that can communicate information between thedatabases DB(1), DB(2), . . . DB(N). Communications path C allowsdatabases DB(1), DB(2), DB(N) to synchronize with and/or update withrespect to one another so that information acquired and/or stored intodatabase DB(1) by CPU 12(1) can be shared with DPU 12(2), . . . , DB(N)via database DB(2), . . . , DB(N) and vice versa. In one exampleembodiment, databases are provided numbering in X associated with Ndistributed processing units where N>=X and, for cases where X!=1, acommunication link for synchronizing all of the X number of databases isalso provided.

In the example shown, machine M looks to a DPU 12 for support,coordination, control or other functionality. In one exampleimplementation, machine M includes a latency select LS to discover andselect which DPU 12 to use. Selection between DPU 12(1), DPU 12(2), . .. , DPU(N) is based on how long it takes for machine M to receiveresponses. For example, machine M can send “pings”, substantiveinquiries or other messaging to DPU 12(1), DPU 12(2), . . . , DPU(N) tothereby set up an intentional race condition. Machine M can then choosethe DPU with the fastest response time, e.g., the one that wins therace. Fast response time can indicate (a) low network or othercommunications latency on the communications path between machine M andthe sooner-responding DPU 12; and/or (b) greater processing availabilityof the faster-responding DPU; and/or (c) better availability to thefaster-responding DPU of relevant information needed to respond to themachine M's substantive request. Machine M can select one or severalsooner-responding DPU's 12.

A particular DPU 12 might intentionally delay response if conditionswarrant. Conditions can include but are not limited to availableprocessing time, available memory and available network bandwidth. Inshort, the DPU 12 can delay if there is a shortage of any systemresource ahead of system overload and/or thrashing which would affect inflight event processing. If any system resource is low, it is possibleto delay the response to bias away from that unit. This maintains the 0compute cycle decision making by the client/agent on that end wheredecision latency needs to remain low and resources are likely moreconstrained. In a more extreme situation, one DPU 12(1) might notrespond at all due to damage, malfunction, communications breakdown,prearranged reservation and/or other factors, and machine M maytherefore select the other DPU's 12(2) that do respond.

Any number of DPUs 12(1)-12(N) may communicate with machine M over anynumber of communications paths some of which can be different fromothers (e.g., some paths might be via the Internet or other network,other paths might be over leased, satellite or other dedicated orsemi-dedicated communications links, and still other paths might be viaalternate communications links such as point-to-point radio or microwavecommunications, power line telecommunications or other techniques).Machine M can be, comprise, or be coupled to an Agent 18 andcommunication is facilitated through an Agent Adapter 16 in thediagrams. For ease of understanding and reading, we will infercommunication directly to a machine M with the understanding the machineM is or can be an Agent 18 and the agent adapter is the facilitator ofthose communications to and from the distributed processing units(diagrammed as DPU 12).

Machine M may cooperate with more than one distributing processing unitand rely on different distributing processing units for the same ordifferent things. For example, one distributed processing unit mayprovide real time event processing and control whereas for anotherdistributing processing unit may serve as a resource for storage,sensing or the like.

Once machine M selects a DPU(s) 12, it may continue to operate with thatDPU(s) unless or until that DPU(s) fails, has increased latency orotherwise becomes a less optimal choice. During ongoing operations,machine M may continue to check latency to determine whether the DPU(s)12 it is cooperating with is the best choice. If machine M determinesthat it would be better to cooperate with a different DPU(s) 12 (or ifthe DPU the machine has been cooperating with fails or otherwise becomesunavailable), machine M can change its selection and begin cooperatingwith a different DPU(s). Communications C between the respective DPUdatabases DB(1), DB(2) can be used to ensure that the respectivedatabases are synchronized so that any DPU 12 can pick up where theother DPU left off without delay. Such communications C betweendatabases DB(1), DB(2) can be conducted continually, intermittently,constantly, on demand or otherwise.

FIG. 1A shows a further embodiment wherein DPUs 12(1), . . . , 12(N)communicate with various machines via a streaming network 14. Streamingnetwork 14 can be used to provide secure communications between DPUs 12and/or to allow an external control or other arrangements to communicatewith some or all of the DPUs. In the example shown, each DPU 12 usesnetwork 14 to communicate with one or more Agent Adapters 16(1), 16(2),. . . , 16(M). In some example implementations, each DPU 12(x) cancommunicate with a single Agent Adapter 16(x). In other implementations,more than one DPU 12(x), 12(y) can communicate with each Agent Adapter16(x). In still other implementations, there can be more than one AgentAdapter 16(x), 16(y) for each DPU 12(x).

Non-limiting embodiments are also designed to be implemented inredundant manner, so when there are multiple DPUs 12 available, an AgentAdapter 16 can fail-over automatically from DPU 12(x) to DPU 12(y)during an outage. In this way, the system provides a robust andredundant overall ecosystem. The technology also allows for “hot”deploys/removals. This means the system can be expanded or contractedquickly with minimal cost. As will be explained below, a selectionalgorithm is used to select which DPU 12 is to be used to send eventsto, control or otherwise communicate with any given Agent Adapter 16.

In the example shown in FIG. 1A, DPUs 12 can work through Agent Adapters16 to access and/or control Agents 18, which in turn interact withsystem 20. Each Agent Adapter 16 communicates with one or more Agents18. As will be detailed below, Agents 18 can interact with a System 20of arbitrary breadth and complexity in any of a variety of ways. SomeAgents 18 can control aspects of System 20, other agents can senseaspects of System 20, and still other agents can perform otheroperations in connection with System 20. Any given Agent 18 can performany or all such functions.

The FIG. 2A embodiment can be used to provide a cloud-based highlyscalable solution with a high degree of automation that works with ahomogeneous or heterogeneous set of elements. FIG. 2A shows a moredetailed diagram of an example DPU 12(x) coupled to streaming network14, which in turn is coupled to Agent Adapter 16(x) via a WirelessAdapter 69. Agent Adapter 16(x) is coupled to System Agent 18(x), whichis coupled to or is part of system 20. In the example shown, DPU 12 maycomprise one or more central processing units [CPU(s) 52], which canexecute instructions stored in non-transitory Persistent Storage 54 andcan Access Memory 56. One or more network interfaces permit DPU 12(x) tocommunicate with and via Network 14. An interface device 60 may providean application programming interface (API) and/or user interface (UI) toprovide input/output for DPU 12. An example non-limiting DPU basedsystem is a Machine to Machine (M2M) interface that is faster, moreredundant, scalable and can handle unlikely edge cases. In theecosystem, any like or other DPU can back up any other, making thesystem exceedingly robust.

Agent Adapter 16 similarly may comprise one or more CPU's 62 coupled topersistent non-transitory storage 64 and memory 66. Network Interface 68permits the Agent Adapter 16 to communicate with Network 14 (in theexample shown, at least some such communications is wireless viawireless adapter 69). System Agent 18 also comprises one or more CPUs 70coupled to Persistent Storage 72, memory 74 and Network Interface 76. Inthe example shown, DPU 12 communicates via Network 14 with Agent Adapter16, which in turn communicates with System Agent 18. System agent 18(x)in the example shown includes CPU(s) 70, Persistent Storage 72, memory74 and Communications Adapter 76. In the example shown, Agent Adapter16(x) and System Agent 18(x) cooperate to exert control over and/orreceive information from System 20. In some example embodiments, SystemAgent 18(x) and Agent Adapter 16(x) may comprise a single or distributedunit sharing resources.

FIG. 2B shows a variation of the FIG. 2A embodiment omitting theWireless Adapter 69 within Agent Adapter 16(x) and instead using variousother network adapters in parallel for supporting communication betweenDPU 12(x) and the Agent Adapter.

FIG. 2C shows a further non-limiting implementation where the AgentAdapter 16 is embedded into System Agent 18. One DPU 12(x) supports andinteracts with plural System Agents 18(x), 18(y) directly.

FIG. 2D shows a further example of an embedded (e.g., chip based orother) implementation wherein the System Agents 18 each include aWireless Adapter 69 enabling independent wireless communication with DPU12(x) (in this case Streaming Network 14 may be a wireless streamingnetwork).

FIGS. 3A-3C show extended systems with many DPUs 12, Agent Adapters 16and Agents 18. As can be seen, a DPU 12(1) may be coupled to three AgentAdapters 16(1), 16(2), 16(3) each of which is coupled to an associatedrespective Agent 18(1), 18(2), 18(3). Any given DPU 12 may beoperatively coupled or associated with any number of Agent Adapters 16.FIG. 3B shows a particular example where the Agents 18 provide powergrid control functionality through Wind Farm 18(2), Solar Farm 18(3),Breaker 18(6), Hydroelectric Plant 18(9), Coal Plant 18(10), Substation18(11), Home Photo-voltaic (solar cell) system 18(18), and the like.FIG. 3C shows a further particular example where agents operate a farmand include farm machinery and equipment such as Tractor 18(1), Combine18(2), Hay Baler 18(3), Farm Perimeter and Soil Sensors 18(4), WeatherStation 18(6), Satellite 18(18), and the like.

FIGS. 4A-4B show a scenario where a DPU 12(1) fails. In the exampleshown, each Agent 18 connects to the nearest and/or least loaded DPU 12.Thus, Agent 18(1) may contact, connect to and begin operating with DPU12(1). However, as shown in FIG. 4B, when DPU 12(1) fails, work isdiverted seamlessly to the next nearest and/or lightly loaded DPU 12such as DPU 12(2). In this case, “nearest” may mean physically closestor closest in terms of network connectivity. For example, in some casesa more direct path across a network may exist between nodes that areactually physically more distant. By way of analogy, it may be easier tofly from New York City to Los Angeles than to fly from New York to TylerTexas even though Tyler is physically closer to New York than is LosAngeles. In this analogy, Los Angeles may be considered “closer” to NewYork from a network standpoint even though it may be a further actualdistance. Similarly, bandwidth considerations may also apply so that theavailability of a higher bandwidth path may (depending on the amount ofdata to be exchanged) make one DPU 12 preferred over another even if thephysical, routing or other distance is actually greater.

FIG. 5 shows Agent Adapter DPU Registration. In this particular example,an Agent Adapter 16 generates processing request. The Agent Adapter'sDPU Requester 19 multi-casts/broadcasts the DPU request over Network 14to DPU's 12. The DPU's 12 each respond by replying back over the Network14 back to the DPU Requester 19. In one example embodiment, the DPURequester 19 selects the first response received (suppose for purposesof this example that DPU 12(N) responds first) and passes the connectioninformation on to the Agent Adapter 16. When the next system eventoccurs, the Agent Adapter 16 sends the associated event to thepreviously-selected DPU 12(N). Thus, DPU Selection in one non-limitingembodiment uses a Broadcast Request Reply design pattern to select theoptimal processing unit.

FIG. 9 shows this process in more detail. Starting at the upper lefthand corner of the diagram, Agent Adapter 16 sends request to DPUs12(1), . . . 12(N). Agent Adapter 16 establishes a connection with thefirst-responding DPU 12(1). If/when the connection is later lost, AgentAdapter 16 repeats the process and establishes a new connection withfirst-responding DPU 12(2). The DPU 12 Requester 19 and Responder 6 areimplied in this example.

An example request contains the System Agent type. If the System Agenttype is supported by a given DPU 12, the DPU's Responder 6 processresponds with the information needed for that DPU 12's Connector 101(see FIG. 6). The Requester 19 will accept the first response as beingthe optimal choice using the latency of the response to be the decidingfactor. The Requester 19 will pass the information on to System Agent 18supplying the connectivity information. Once that is chosen, requestsare made to the selected item DPU 12 via an associated Connector 101.This process can and should be repeated periodically to make sure theoptimal DPU 12 is selected. In the case where a response to a requestdoes not happen fast enough or events are not acknowledge, thisprocedure should be repeated immediately and the event or requestresent. (See FIG. 5.)

As shown in the FIG. 7 example Event Processor to Reactor (DPU internal)registration, Event Reactor 103 is the registrar for events that EventProcessor 104 is interested in. Event Processor 104 may register withEvent Reactor 103 for multiple events.

FIG. 6 shows non-limiting event processing including the followingcomponents:

-   -   1. Connectors 101—Controls communication between the system and        machines and data sources.    -   2. Transformers 102—Transforms messages from different machines        into a common format    -   3. Event Reactor 103—Takes events from different data sources        (including machines) and routes them to appropriate processors.    -   4. Event Processors 104—Registers for various events, analyzes        the input and takes actions.    -   5. Commanders 105—Sends commands to different systems in the        ecosystem and allowing them to access in a common way.    -   6. Agent Adapters 16—Connections and handles communications        between the System Agent 18 and the DPU 12.    -   7. System Agent 18—An external device or system that sends        events and/or can be controlled by the system. This can be a        System Element or another system all together (SoS arrangement).    -   8. DPU 12—Collection of items 1-5 that works as a single        processing unit.

In the example shown in FIG. 10, the System Agent 18 sends messages andevent information through Agent Adapter 16 and Connector 101 (FIG. 8block 202) which in turn sends messages and events to Transformer 102 toallow them to be transformed (FIG. 8 block 204) into a common, systemspecific format. Transformer 102 sends system specific events to EventReactor 103 for distribution to Event Processors 104 (FIG. 8 block 206)and if necessary, discovery of handlers (there may be more than one).Event Processor 104 receives events it has registered for from the EventReactor 103, analyzes the data and, when analysis dictates, takes one oftwo actions (FIG. 8 blocks 208, 210):

1) Sends data back to Event Reactor 103 as a new type of event(recursive call); or

2) Sends a command or commands to Commander 105 to take action or pollfor information from System Agents 18 through Connector 101. Connector101 sends any responses from System Agent 18 back to Commander 105 whichin turn returns a possibly modified response to Event Processor 104.(See FIG. 6; FIG. 8 blocks 214, 216, 218). Depending on the response,more commands may be sent to any required System Agent 18 if needed(this is also possible for sending back super events). This continuesuntil the event handling is satisfactorily completed. It is alsopossible that after commands/replies are compete, option 1 may beinvoked and a new event sent to the reactor. This encompasses bothactions 1 and 2 respectively.

The example System 10 allows elements/agents to be connected andcontrolled by a selected DPU(s) 12. The type of control and the type ofelements/agents can vary depending on the particular application. Thisis a framework to use in multiple industries for wide area control overdisparate systems working in a common ecosystem. There are four parts todescribing a working system:

1. Define the abstract methods or representation for a problem domain(abstract Commander 105 and Transformer 102).

2. Define the concrete Commander 105 and Transformers 102 for eachSystem Agent 18 types for a given digital ecosystem.

3. Create or configure concrete Connectors 101 for each System Agent 18type.

4. Describe the defined system interactions. This is accomplished withparticular implementations of Event Processors 104. This also maypossibly discover abstract Commander 105 methods and use particularimplementations of those methods per commander 105 type.

Once the DPU 12 is ready to use for a given digital ecosystem, thesystem interactions start.

The first step is for an Agent Adapter 16 to decide the optimal DPU 12to use. In one example embodiment, this is done using the BroadcastRequest-Reply design pattern. The request can be sent by the DPURequester 19 to all Responders 6 on DPUs 12 via Multicast/BroadcastNetwork 14 with a payload of the System Agent 18 type. All DPUs 12 withsupport for the System Agent 18 type return a response to the DPURequester 19. The first response to the request will be the selected DPU12. The DPU Requester 19 will pass on the information to the AgentAdapter 16 to allow requests to be made directly to the selected DPU 12.This process should be repeated periodically to ensure the optimal DPUis being used. The process will also be repeated on connectivityfailure.

Once that is decided, System Agent 18 events are sent to the Connector101, generalized through the Transformer 102 and passed on to the EventReactor 103. The Event Reactor 103 uses a Reactor design pattern toallow Event Processors 104 to register for events they are interestedin. The Event Reactor 103 then brokers events to the interested EventProcessors 104 to be evaluated and potentially acted upon.

The Event Processor 104 takes events potentially from multiple datasources and processes them. This can be done with simple conditionallogic, more complex AI algorithms, through an analytics engine or anyother method or combination of methods possible. If the Event Processor104 deems action needs to be taken based on received information, one oftwo things can be done:

1) The Event Processor 104 may create a super event that can be fed backinto the Event Reactor 103 for processing by other Event Processors forfurther analysis; or

2) It can send commands through the Commander 101 and then Connector 101to various elements to either gather more information directly fromSystem Agents 18 or send commands to take automated action on SystemAgent(s).

Choice 2 may also invoke choice one based on the response. In thatsituation, both commands are sent and a super event created.

At this point the event has been received, processed and acted upon.

Below are the common logic gates for the abstract system:

Event Reactor 103—Given an event, for each Event Processor 104registered for that event type, send the event.

Event Processor 104—Given event(s), if a threshold is violated,either: 1) create a new event to the Event Reactor 103; 2) send commandsto the Commander 105 which in turn sends specific commands to a thegiven System Agent 18; or 3) Combine 2 and 1 to send commands and thencreate a new event based on the response(s).

DPU Requester 19/Responder 6—The Requester 19 sends a request to allResponders 6 with the System Agent 18 type for the request. If the DPU12 supports the System Agent 18 type, the Responder 6 within the DPU 12returns connection information for that DPU's Connector 101 for thegiven System Agent 18 type. The first response is selected.

The first step to creating a solution for a given industry or problemdomain is to define the high level events and commands to be supported.Once those are well understood, abstract classes for the Commander 105and Transformer 102 are created. There may be several classes of eventsand controls so there might be more than one abstract class defined.Next, concretely define the Commander 105 and Transformer 102 classesper System Agent 18 type.

Once those are defined, the communications protocols to be used can beunderstood. Connectors 101 for each communication protocol to beencountered needs to be added or, if not available, created/developedfor the code base.

The next step is to create the Event Processors 104 and the logic neededfor taking action on given generic events. Functionality may beidentified based on particular applications by industry users and whatthey desire to automate, control and/or report on.

Once those programming steps are complete, we are ready to create aphysical DPU 12. The DPU 12 consists of an independent computer systemwith a CPU, storage, memory and connectivity (networking) plus aninstalled version of the code base created earlier.

A Multi-cast/Broadcast network 14 will then be established and the DPU12 Requester 19 and Responder 6 configured to use it.

Once DPUs 12 are created, the physical unit needs to be connected to andconfigured for the Network 14. The System Agent 18 will also needconnectivity to this Network 14. To accomplish this, the System Agent 18connects directly, over a Local Area Network (LAN), through a serialinterface or any other connectivity method conceivable to the AgentAdapter 16. The Agent Adapter proxies all System Agent 18 to DPU 12communications. Once this is complete and communication verified, theassimilation of the System Agent 18 into the MAS 10 is complete.

One optional component would be the Requester 19/Responder 6. The systemcan be used without it but use of such components adds to systemrobustness and scalability features. The example non-limiting embodimentalso provides System Agents 18 to be configured with DPU connectioninformation, making the system more brittle as each element will bebound to a DPU 12 or need to maintain connectivity information for allDPUs 12.

Conversely, the Requester 19/Responder 6 can be used standalone forother frameworks or systems. It can in fact, in one embodiment, it canbe used as its own component to distribute load across a bank of web orother services.

Other optional components are the Transformer 102 and Commander 105.These would be optional in a situation where all events and commandswere the same for all elements or the elements were different enoughthat there was no commonality. In these cases, the Connector 101 couldpass events directly to the Reactor 103 and the Event Processor 104 cansend commands directly to the Connector. You might see this where theexample non-limiting framework is used for a SCADA system or plantautomation where all System Agents 18 are machine elements and each isunique and/or containing sets of homogeneous elements from avendor/command perspective or they are using a protocol standard that iswell adhered to.

In a wide area configuration, to make the system exceedingly secure andensure the lowest possible network latency, the DPUs 12 can be connectedacross a private line transport Network 14. This allows the purveyor ofthe System 10 to completely control the network and data. The SystemAgents 18 could also be added to this network through private lines toincrease the security of the network. Bastion hosts could be added toallow access from the public Internet for when desired. The bastionscould also work as a fall back to the public Internet in the case ofprivate network disruption or connectivity issues.

It is possible to spread the DPU 12 components across separate computerscreating a cluster or bank of functionality for each component.Components could be mixed or separated depending on parallel and/orreal-time processing needs. This would be lucrative if one component wasrequiring a lot of processing while others need guarantees against beingblocked. In this case, the DPU 12 Requester 19/Responder 6/can be reusedto facilitate load balancing across the cluster. This also has otheraforementioned benefits of hot deploys/removal of computing resourcesand robustness at a component level.

This type of configuration would be very likely in situation with highlevels of automation or learning AI that requires massive processing. Inthese examples the Event Processors could be run on a large cluster ofcomputers while the other elements are run on more modest hardware. Thisallows the bulk of the processing to be handled with potentially massiveprocessing resources while the rest of the components could probably bewell served on a single computer. This also ensures that the potentiallarge processing needs of the Event Processor 104 will not interferewith the critical and time sensitive act of receiving events.

EXAMPLE I

Example I controls an electrical grid. The flow of the electrical gridis controlled by dispatch centers. The system would initially beengineered to enhance the dispatching centers but, as iterativedevelopment increases capabilities, eventually those centers should bephased out.

The real utility comes with the advent of smart grids. The amount ofdata such as weather, spot utilization from appliances, supplementalenergy from home solar panels and other data considerations makes itincreasingly difficult if not impossible for human agents to accuratelyprocess all the information in a timely manner Handling this as a DPU 12MAS 10 solves this problem and allows the data to be processed andreacted to near real time.

To do this in an optimal manner, the DPUs 12 should be distributed in awide geographic region. In this way, this system increases therobustness of the electrical grid's MAS 10. Instead of a single dispatchcenters for an area, multiple DPUs can be deployed over a widegeographic region. This can be done at a fraction of the cost of runningdispatch centers.

While the energy grids are one example, the present technology can beapplied to any grid/network problem. There are many industries thatwould benefit equally well from automation in a wide area.

Additionally, on a smaller scale, a specific utilization can be burnedonto chips and used in embedded systems or included as subsystems with amicrocomputer. The example technology can now be used to control andautomate any single unit that reacts to events and requires automation(cars, planes, robots, . . . ). The DPU 12 MAS 10 solution also allowsfor redundancy and automatic fail-over even at a small area single unitMAS level.

EXAMPLE II

FIG. 11 show a further example of a motor vehicle using MAS 10 tocontrol critical systems. In the example shown, MAS 10 keeps criticalsystems working in the event of accident damage. In particular, DPU12(1) may perform traction control, auto braking and other criticalsafety features. DPU 12(3) could act as the anti-lock brake agent (thisDPU is likely to be an embedded processor in such an application).Airbag agents are also connected through the vehicle's wired or wirelessNetwork 14, and brake sensors and controls are connected through thevehicle's network. In the event of an accident that damages a DPU 12,the MAS 10 immediately recovers when affected airbag Agent 18 uses theAgent Adapter 16 to establish a connection with alternative DPUs 12.

Other example applications:

Water Utility Coordination and Dispatch

Oil and Gas Coordination and Dispatch

Network operations automation

Network Access Service Request (ASR) Automation

Defense System Control, Coordination and Automation

Robots

Drones

SCADA

Automated Safety Systems for automobiles and airplanes

Exchange and Trading Automation

Medical Systems Coordination and Automation

Machine to Machine Controller

System of System Controller

Any MAS That Requires Event Driven Coordination and Automation

While the invention has been described in connection with what ispresently considered to be the most practical and preferred embodiments,it is to be understood that the invention is not to be limited to thedisclosed embodiments, but on the contrary, is intended to cover variousmodifications and equivalent arrangements included within the spirit andscope of the appended claims.

The invention claimed is:
 1. A distributed secure communications andcontrol system comprising: a distributed arrangement of intelligentagents each connected to at least one respective sensor, the distributedarrangement of intelligent agents being configured to generate events inresponse to the respective sensors for secure communication to andprocessing by a distributed processing and control architecture; adistributed processing and control architecture comprising: eventreactors that broker events generated by the distributed arrangement ofintelligent agents for routing to dynamically changing selections ofdistributed event processors, and distributed event processors beingstructured to process the routed events and responsively supply commandsfor action and responses; and a secure streaming network configured tosecurely communicate the generated events between the distributedarrangement of intelligent agents and the distributed processing andcontrol architecture using security based at least in part on OTPs (OneTime Pads).
 2. The system of claim 1 wherein the distributed arrangementof intelligent agents select distributed event processors by setting upintentional race conditions between said distributed event processorsand measuring race responses.
 3. The system of claim 1 further includingan event dispatcher that dispatches events to handlers provided by thedistributed event processors.
 4. The system of claim 1 further includinga transformer that transforms events for use by the distributed eventprocessors.
 5. The system of claim 1 further including eventtransformers that transform events generated by the distributedarrangement of intelligent agents for processing by the event reactorsand the distributed event processors.
 6. The system of claim 1 wherein:the event reactors are configured to: receive an event from anintelligent agent; transform the event; and dispatch the event to atleast one distributed event processor; and the at least one distributedevent processor is configured to: handle the event; discover anintelligent element; and send commands to the discovered intelligentelement for action and response.
 7. The system of claim 1 wherein: thedistributed intelligent agents are configured to forward agent eventsthrough a connector and a transformer to the event reactors; the eventreactors are configured to analyze the event(s); and the distributedevent processors are configured to generate one or more intelligentelement commands in response to the analyzed events, discover one ormore intelligent elements to send the commands to and securely forwardthe intelligent element commands to the discovered one or moreintelligent agents using a secure streaming OTP protocol, and checkresponse(s) and send more commands if needed.
 8. The system of claim 1wherein the distributed event processors are configured to delayresponse based on resource availability.
 9. The system of claim 8wherein the resource comprises at least one of processing time, memoryand network bandwidth.
 10. The system of claim 1 wherein the distributedevent processors are configured to create, in response to events, superevents that are fed back into the event reactor for processing by otherdistributed event processors.
 11. The system of claim 1 wherein some ofthe distributed event processors comprise clusters of computers runningmachine learning, and others of the distributed event processorscomprise single computers.
 12. A distributed communications and controlsystem comprising: N distributed event processors, N>1; an OTP (One TimePad) secured network coupled to the N distributed event processors; anagent coupled to the network and to at least one sensor, the agentconfigured to securely send messages to dynamically changing ones of theN distributed event processors over the OTP (One Time Pad) securednetwork, and determine, based on replies thereto, the ones of the Ndistributed event processors that respond; the agent being configured tosend further messages to at least one of the responding N distributedevent processors via the OTP secured network; the agent establishing acontrol relationship with the selected at least one distributed eventprocessor.
 13. The system of claim 12 further including a databaseassociated with each of N distributed event processors, and a securecommunication link for synchronizing the N databases.
 14. The system ofclaim 12 further including databases numbering in X associated with Ndistributed event processors where N>=X and, for cases where X !=1, anintermittent communication link for synchronizing the X number ofdatabases.
 15. The system of claim 12 wherein the intelligent agentdetermines the winner of an intentional race condition between the Ndistributed event processors.
 16. The system of claim 12 wherein theintelligent agent repeats selection upon detection that the selecteddistributed event processor is no longer reachable.
 17. The system ofclaim 12 further including event reactors, and a transformer thattransforms events for processing by the event reactors.
 18. The systemof claim 12 wherein the N distributed event processors are configuredfor: receiving events from agents; transforming the events; dispatchingevents to handlers; handling the events; discovering an agent capable ofacting on a command; and sending the discovered agent commands foraction by the discovered agent.
 19. The system of claim 12 wherein the Ndistributed event processors are configured to create, in response toevents, super events that are fed back for processing by others of the Ndistributed event processors.
 20. The system of claim 12 wherein some ofthe N distributed event processors comprise clusters of computersrunning machine learning, and others of the N distributed eventprocessors comprise single computers.